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UID:pretalx-scipy-2026-TBDWJZ@pretalx.com
DTSTART;TZID=CST:20260717T104500
DTEND;TZID=CST:20260717T111500
DESCRIPTION:Graduate textbooks in applied mathematics are notoriously inscr
 utable\, dense with symbolic derivations never connected to intuition\, ap
 plication\, or executable code. This talk presents a teaching pattern: Mot
 ivate\, Symbolize\, Derive\, Lambdify\, Simulate\, Validate. The infrastru
 cture is stable self-contained marimo notebooks with tests and automated p
 ublishing via GitHub Actions. Within the notebook\, SymPy handles the symb
 olic stages\; NumPy\, SciPy\, and matplotlib handle numerics and visualiza
 tion. We demonstrate the pattern through a complete interactive treatment 
 of Isaacs' Homicidal Chauffeur\, a classical pursuit-evasion differential 
 game\, and close with an invitation to collaborate on open-source educatio
 nal content in advanced applied mathematics.
DTSTAMP:20260622T110113Z
LOCATION:Johnson Great Room
SUMMARY:Derivations\, Not Just Simulations: Teaching Applied Mathematics wi
 th Scientific Python - Michael Zargham
URL:https://pretalx.com/scipy-2026/talk/TBDWJZ/
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